48 results about "Process automation system" patented technology

The invention discloses a mold injection molding full-process automation system based on layered cooperative control, which comprises a central control layer, a module scheduling layer and an equipment execution layer, and clock synchronization among the layers is realized through an industrial Ethernet. The central control layer comprises a dynamic scheduling server and a digital twinborn verification module, the module scheduling layer comprises a mold intelligent scheduling module, an injection molding process control module and a product quality closed loop module, and the equipment execution layer comprises a manipulator cooperation unit and a sprue material processing unit. By constructing a three-layer cooperative control architecture of a central control layer, a module scheduling layer and an equipment execution layer and combining a modular hardware carrier and a cross-layer data closed loop, common industrial problems such as cooperative level splitting, mold control marginalization and abnormal response delay are systematically solved; and finally, the comprehensive benefits that the die changing efficiency is remarkably improved, the product reject ratio is greatly reduced, and the energy consumption is obviously reduced are achieved.

An advanced AI system, known as Bayesian Graph-Based Retrieval-Augmented Generation with Synthetic Feedback Loop (BG-RAG-SFL), combines Bayesian evaluation, graph-based retrieval, and synthetic data feedback to create a continuously improving AI platform. The present invention integrates multiple LLMs, optimizing their performance while managing complexities across different models. Key features include a knowledge graph-based RAG system, a Bayesian evaluation network, a secondary ground-truth graph for verification, synthetic data generation for ongoing improvement, and a multi-agent verification system. The system also functions as an AI operating system capable of acting as a virtual user with screen I / O control and managing multiple computers as an intelligent process automation system.

A VCN process may receive information associated with a value chain network. A VCN process may provide the information to a set of Artificial Intelligence (AI)-based learning models, wherein at least one member of the set of AI-based learning models is trained to classify at least one of: an operating state, a fault condition, an operating flow, or a behavior of the value chain network and at least one member of the set of AI-based learning models is trained on the training data set to determine, upon receiving the classification of the at least one of: the operating state, the fault condition, the operating flow, or the behavior, a task to be completed for the value chain network. A VCN process may configure a robotic process automation system to execute the task to facilitate an improvement in the value chain network.

The invention belongs to the technical field of electric digital data processing, and discloses a dynamic strategy configuration-based cancel-after-verification process automation system, which comprises the steps of obtaining cancel-after-verification interaction information, performing scene feature extraction and strategy element deconstruction, and forming a strategy element knowledge base; analyzing the voucher identification code, performing multi-dimensional voucher attribute deconstruction and type portrait description, and generating a voucher intelligent portrait; performing rule matching degree evaluation and strategy source tracing, and locking an applicable strategy rule set; performing strategy conflict harmonic analysis and rule priority ranking to generate a cancel-after-verification execution instruction chain; performing flow wave crest prediction and resource scheduling arrangement to form a load balancing strategy table; performing intelligent channel shunting scheduling, and establishing a cancel-after-verification process execution network; according to the invention, the intelligent automation of the cancel-after-verification process is realized, the system processing efficiency is improved, and the method can adapt to complex and changeable business scene requirements.

Implementations relate to storing, in alarms database for a process automation system, an association of an alarm configuration file to a function block identifier of a function block that corresponds to the alarm configuration file. Some implementations relate to a node transmitting, via a process automation network, an alarm configuration request that includes the function block identifier and receiving, in response to the request and via the network, the alarm configuration file. The node can include the function block identifier in the alarm configuration request based on the corresponding function block being executed by the node and / or being utilized in alarm monitoring by the node. Some implementations additionally or alternatively relate to receiving the alarm configuration request, and identifying the alarm configuration file based on it being stored, in the alarms database, in association with the function block identifier of the alarm configuration request.

An AI-based platform for enabling intelligent orchestration and management of power and energy is provided herein. The AI-based platform includes a set of adaptive, autonomous data handling systems, wherein each of the adaptive, autonomous data handling systems is configured to collect data relating to energy generation, energy storage, energy delivery, and / or energy consumption, wherein the data is collected from a set of edge devices that are in operational control of a set of distributed energy resources; and a set of intelligent agents configured to, by robotic process automation, autonomously adjust, based on the collected data, a set of operational parameters for such operational control.

A value chain system that provides recommendations for designing a logistics system generally includes a machine learning system that trains machine-learned models that output logistics design recommendations based on training data sets that each respectively defines one or more features of a respective logistic system and an outcome relating to the respective logistics system; an artificial intelligence system that receives a request for a logistics system design recommendation and determines the logistics system design recommendation based on one or more of the machine-learned models and the request; and a digital twin system that generates an environment digital twin of a logistics environment that incorporates the logistics system design recommendation, and one or more physical asset digital twins of physical assets. The digital twin system executes a simulation based on the logistics environment digital twin, the one or more physical asset digital twins.

This application provides a method, apparatus, storage medium, and electronic device for reviewing merchant annual inspection work orders, relating to the field of work order review technology. It enables automated review of merchant annual inspection work orders, shortening the review cycle, improving review efficiency, enhancing the standardization and objectivity of the review process, and further improving the accuracy of the review results. The method includes: automatically logging into a merchant annual inspection work order system through a robotic process automation system to obtain a target annual inspection work order for a target merchant and a corresponding image for review of the target merchant. The target annual inspection work order includes the annual inspection items to be reviewed and the registration information of the target merchant. The image for review is processed using a visual large-scale model based on preset information processing rules to obtain structured information corresponding to the annual inspection items to be reviewed. The structured information and registration information are compared according to preset review rules for the annual inspection items to be reviewed to generate the review result for the target merchant.

Systems and methods for detecting and predicting faults in an industrial process automation system use trend data to forecast alerts and allow action to be taken before a problem occurs. The systems and methods provide fault / failure predictions that improve over time as more empirical data is collected for a related set of system components. The systems and methods may identify relationships among the components of a process automation system; identify and collect changes to system configuration; identify and collect data to inform reliability and predictive models; develop a domain-specific predictive model for one or more components that allows for component-based failure or degradation prediction; develop a system-predictive model that leverages reliability and criticality relationships, component-based predictions and operating parameters to predict the health of a part of or the entire process automation system; deliver a prioritized alert system; and identify root-cause failures of a component.

The invention relates to a method for diagnosing a situation in a process automation system (1). A field device (2) is installed in the system (1) and data about the system (1) are provided. Based on the data and on the basis of a prototype associated with the field device (2), a system model is generated using artificial intelligence. On the basis of a measured value generated by the field device (2), a statement about a situation in the system (1) is generated using the system model.

A document process automation system includes a user interface for uploading a document and invoking an artificial intelligence (AI) content assistant. When invoked, a chat window for the Al content assistant is displayed. The Al content assistant leverages a chat service to enable querying a status of the document through the chat window. The system further includes a document enrichment module, an inbound application programming interface (API), and a document API. The document enrichment module determines a category of the document and attaches attributes associated with the category to the document. The inbound API reads the document and creates a copy of the document for a document management system. The document API reads status updates to the copy of the document from a document queue and updates the attributes associated with the document. The user interface is configured for presenting the attributes thus updated as properties of the document.

Implementations relate to receiving, from a distributed control node (DCN) that includes a corresponding active alarm engine, an alarm configuration transmission that includes a network addressable DCN identifier of the DCN and also includes a direct or indirect indication that the DCN is implementing alarm monitoring that is based on function block(s) of a process automation system. Implementations further relate to, in response to receiving the alarm configuration transmission and determining that no persistent connection-oriented communication session is established between an alarm viewer and the DCN indicated by the addressable DCN identifier of the alarm configuration transmission, causing the alarm viewer to establish a persistent connection-oriented communication session with the DCN using the addressable DCN identifier.

Systems and methods of robotic process automation including: receiving a multi-threaded task request from a messaging application; automatically dividing the multi-threaded task request into a plurality of subtasks based on metadata associated with the multi-threaded task requests; generating a queue comprising one or more subtasks from the plurality of subtasks; identifying an application programming interface associated with the one or more subtasks from the queue; routing the one or more subtasks to the application programming interface; receiving a response from the application programming interface associated with executing the one or more subtasks; and providing the response to the messaging application.

The invention relates to a process valve device (2) for process automation, comprising a valve element (6) for influencing a process fluid, in particular a liquid to be dispensed, preferably metered, wherein the process valve device (2) has a pneumatic drive section (7) for driving the valve element (6), wherein the drive section (7) comprises a piston (8) coupled to the valve element (6) and at least one pressure chamber (9) acting on the piston (8), wherein the process valve device (2) further comprises a control device (19) which is configured to perform position control for positioning the piston (8) and / or valve element (6) along a positioning path by pneumatically actuating the at least one pressure chamber (9), in order to thereby influence the process fluid with the valve element (6).

The invention provides a risk screening method which can be applied to the technical field of artificial intelligence or big data. The method comprises the steps of obtaining message data of a customer in response to a transaction request of the customer; performing hit processing on the message data based on a predefined target list to obtain a target message and corresponding hit information, and uploading the target message and the hit information to a pre-trained natural language processing model through a process automation system; judging the hit information by using a natural language processing model to obtain a judgment result of the target message, and transmitting the judgment result back to the process automation system; and marking the transaction processing result of the customer through the process automation system based on the judgment result. The invention further provides a risk screening device and equipment, a storage medium and a program product.

Systems, methods and apparatus for a robotic process automation system for consolidating a set of loans are disclosed herein. An example system may include a set of data collection and monitoring services for collecting information about a set of loans and for collecting a training set of interactions between entities for a set of loan consolidation transactions; an artificial intelligence system that is trained on the training set of interactions to classify a set of loans as candidates for consolidation; and a robotic process automation system that is trained on a set of loan consolidation interactions to manage consolidation of at least a subset of the set of loans on behalf of a party to the consolidation.

The application discloses a kind of based on deep learning's borehole underground television image structure surface parameter rapid extraction method, it is related to computer vision and deep learning technical field in engineering geological survey, this method fuses YOLOv11 target detection, Canny edge extraction, K-means clustering and sinusoidal curve fitting technology, constructs the full-process automation system from image input to parameter output.The application realizes high-precision structure surface positioning by YOLOv11, Canny operator completes edge refinement extraction, K-means clustering realizes the automatic decoupling of multiple structure surfaces, and the automatic calculation of structure surface tendency, dip angle and joint spacing is realized by sinusoidal fitting combined with space coordinate conversion.The application does not need manual intervention, processing efficiency is high, parameter precision is high, robustness is strong, can be widely applied to the intelligent interpretation of borehole image in various geotechnical engineering geological survey, significantly improves the survey efficiency and data reliability.

Documentation may be used to automatically create a set of scripts to be executed by a robotic process automation system. A machine learning engine may be used to identify patterns in a first documentation and to then derive a flowchart descriptive of a documented process, subprocess, or combination thereof. The flowchart is compiled into a script executable by the robotic process automation system.

Implementations are described herein for leveraging an “out-of-band” communication channel between nodes of a process automation system. In various implementations, an out-of-band communication channel may be established between two or more process automation nodes of a process automation system. The out-of-band communication channel may be outside of a process automation network through which the two or more process automation nodes are communicatively coupled with other process automation nodes of the process automation system. The two or more process automation nodes may cooperate with one or more of the other process automation nodes to implement an at least partially automated process. One or more characteristics of the process automation system may be monitored, and based on the monitoring, traffic may be selectively diverted from the process automation network to the out-of-band communication channel.

Generating a digital representation of a process automation system on a cloud-based service platform uses assets integrated into measurement points. The method includes reading TAG information using an edge device, wherein the TAG information is provided in a character chain data type and represents the hierarchical structure of the respective asset. The method also includes transmitting the TAG information to the cloud-based service platform, and parsing the TAG information using an application, wherein a logic is used for the parsing process, and the name of the asset and the name of the measurement point in which the respective asset is integrated are extracted from the TAG information. A structure plan of the system is generated using the application having all of the system measurement points extracted from the TAG information together with all of the assets which are assigned to the measurement points and are extracted from the TAG information.

The invention discloses an automatic production line of bamboo-based wood-plastic composite material curved surface furniture, and belongs to the technical field of furniture manufacturing. According to the technological process, the production line sequentially comprises a raw bamboo split cutting station, a bamboo curtain weaving station, a wood-plastic extruding station, a multi-layer hot-pressing composite forming station, a cooling and shaping station, a precise cutting and milling station, a local gradient heating and mold pressing station, an assembling station, an automatic conveying system and a central control system, wherein the automatic conveying system and the central control system penetrate through the stations. The local gradient heating mold pressing station comprises a local gradient heating device with a plurality of independent control heating units and a precise mold pressing forming machine with a segmented mold closing speed control function. According to the production line, a core station specially designed for forming the curved surface of the bamboo-based wood-plastic composite material is deeply fused with a full-process automatic system, so that the problem that high-quality and high-efficiency manufacturing of the complex curved surface furniture made of the bamboo-based wood-plastic composite material cannot be realized by a traditional production line is solved, and the mechanical property and the shape precision of a product are remarkably improved.

The invention relates to a system (100, 200, 300, 500) for process automation of a manufacturing plant, the system comprising:-a plurality of machines (140, 536) of the manufacturing plant,-a plant machine database (128, 548) comprising control parameters of the machines; -an automation system (103) for automatically operating the machines of the manufacturing plant according to the control parameters in the plant machine database; -an identity provider comprising a user profile of a plurality of remote users not located in the manufacturing plant, and a plurality of local users located in the manufacturing plant,-a visualization engine, the visualization engine is configured to create augmented reality for a local user and virtual reality including digital twins of a factory for a remote user; -a secure interface (142) configured for receiving, from one of the remote users (108), a request to operate at least one of the machines, causing the visualization engine to generate an acceptance request, the acceptance request is a signal that prompts one of the local users (146) to accept the requested operation of at least one of the machines via augmented reality glasses worn by the one local user, the one local user only if the one local user accepts the request. Control parameters (402-408) included in and / or derived from the received requests are stored in a factory machine database, wherein the automation system is configured to perform automatic operations of the machines in accordance with the stored control parameters included in or derived from the accepted requests.

Implementations relate to providing an alarm configuration GUI via which a user can interact in defining corresponding alarms for corresponding function block identifiers of a process automation system. For example, a user can interact with the alarm configuration GUI in selecting a function block identifier and in defining parameter(s) for an alarm configuration file to be assigned to the function block identifier. Some implementations additionally or alternatively relate to transmitting the alarm configuration file to a DCN, for local utilization by the DCN in alarm monitoring based on a function block having the function block identifier. The transmitting can be responsive to determining that the DCN implements local alarm monitoring based on the function block, and the alarm configuration file being assigned to the function block identifier.

The present invention discloses an automation system for the deadweight test process of a finishing rolling looper, comprising a looper and a control tool thereof. The control tool is Engineering Tool 4 software, which is newly program-designed. The control tool triggers action instructions through the PLC program of TC_MS024 in the Engineering Tool 4 software to control the action cylinder of the looper to extend or retract, thereby causing the looper to be lifted or lowered respectively. The present invention also discloses a technical method for automating the deadweight test process of a finishing rolling looper, which is achieved through the automation system. The present invention effectively combines automatic parameter setting and PLC program control to realize process automation, thereby achieving the purpose of automatically completing the deadweight test with one click, effectively improving labor efficiency, accurately completing projects, and reducing the completion time of the deadweight test and the probability of human process operation errors.

An AI-driven robotic process automation system learns and replicates user workflows across web, desktop, and legacy applications using computer vision and machine learning. During training, the system observes user actions with visual and structural UI context, segments the sequence into reusable tasks, and synthesizes a generalized workflow model. At runtime, a hybrid locator fusing vision with DOM / accessibility metadata binds abstract actions to live controls, while a self-healing subsystem detects anomalies and applies recovery actions. A continuous learning loop updates models and task definitions from execution telemetry so automations remain effective as interfaces evolve. The result is resilient “learn-once, run-anywhere” automation that reduces brittle scripting and maintenance overhead.

The invention provides a block chain node-based certificate life cycle automatic alternation method. The method comprises the following steps of (1) performing initialization deployment; (2) certificate generation; (3) state monitoring; (4) triggering condition judgment; (5) executing corresponding operation; and (6) archiving and auditing logs. According to the method, a full-process automation system of intelligent contract driving, trusted oracle machine linkage, cross-chain cooperation and hierarchical authority is constructed, three innovative algorithms are integrated, and high efficiency, safety, compatibility and intelligence of certificate life cycle management are realized.

The invention relates to high-integration titanium-based tantalum coating bone defect restoration intelligent detection equipment, which belongs to the technical field of medical instruments and comprises a base, a precise self-adaptive clamping system, a composite multi-dimensional detection module, a three-dimensional scanning linkage mechanism, an intelligent dynamic regulation and control unit and a depth data processing center, and the precise self-adaptive clamping system, the composite multi-dimensional detection module and the three-dimensional scanning linkage mechanism are arranged on the base, and the intelligent dynamic regulation and control unit and the depth data processing center are electrically connected with the three-dimensional scanning linkage mechanism. The precise self-adaptive clamping system can realize stable fixation of the prosthesis, the composite multi-dimensional detection module integrates multiple detection functions, and the stereo scanning linkage mechanism ensures all-directional detection coverage. The intelligent dynamic regulation and control unit optimizes detection parameters and equipment states in real time, and the depth data processing center carries out fusion analysis and intelligent quality evaluation on multi-source detection data. According to the equipment, a full-process automatic system from prosthesis clamping and positioning, multi-dimensional detection to data processing is constructed, the problems that in the prior art, the detection function is single, precision is insufficient, and the process is tedious are effectively solved, and the quality detection level of the titanium-based tantalum coating bone defect prosthesis is remarkably improved.

An advanced AI system, known as Bayesian Graph-Based Retrieval-Augmented Generation with Synthetic Feedback Loop (BG-RAG-SFL), combines Bayesian evaluation, graph-based retrieval, and synthetic data feedback to create a continuously improving AI platform. The present invention integrates multiple LLMs, optimizing their performance while managing complexities across different models. Key features include a knowledge graph-based RAG system, a Bayesian evaluation network, a secondary ground-truth graph for verification, synthetic data generation for ongoing improvement, and a multi-agent verification system. The system also functions as an AI operating system capable of acting as a virtual user with screen I / O control and managing multiple computers as an intelligent process automation system.